In recent years, an image processing system recognizing a situation around a vehicle by applying analysis processing to an image captured by an on-board camera has been developed as one of preventive safety techniques for preventing an occurrence of a vehicle accident in advance. The image processing system recognizes lines on the road surface (such as a white line and a yellow line), other vehicles, obstacles, road signs, and the like. These recognition results are notified and announced to passengers, or these recognition results are reflected in automatic cruise control, automatic brake control, automatic pilot control, and the like, so that the cruise state of the vehicle is controlled.
By the way, the brightness (the luminance) of an image captured by an on-board camera fluctuates with a shooting time and a cruise environment. For this reason, the image processing system carries out exposure control to correct the brightness of the captured image. For example, in a situation where the illuminance in an image-capturing range is high (in the daytime in the fine weather, under backlight situation, and the like), the image processing system controls exposure time, aperture, sensitivity, and the like to decrease the exposure. On the contrary, in a situation where the illuminance is low (at night, or in the tunnel), the image processing system controls these to increase the exposure.
On the other hand, in a case where a failure occurs in the exposure control due to a malfunction in the on-board camera, it is difficult to recognize target included in an image accurately, and the recognition accuracy may be reduced. Therefore, various techniques have been considered to determine whether the exposure control of the on-board camera is appropriate or not. For example, a method has been suggested to separately provide an illuminance sensor detecting an external illuminance outside of the vehicle and compare the external illuminance and the brightness of the vehicle body portion in the image captured by the on-board camera to determine whether there is a malfunction or not. A method has been suggested to determine whether there is a malfunction or not on the basis of the light quantity of the road surface calculated in view of the exposure time and the exposure gain of the on-board camera (see JP 2005-33680 A, JP 2014-187496 A).
However, in accordance with the above conventional methods, it is difficult to improve the diagnosis accuracy for diagnosing malfunctions. For example, the brightness of the vehicle body portion in the image captured by the on-board camera changes in accordance with not only the external illuminance but also the type of the painting, the surface treatment, the state of dirt, and the like of the surface of the vehicle body. The light quantity of the road surface also changes in accordance with the luminance, the construction state, and the like of the road surface. Therefore, a malfunction may be falsely determined to occur in the image processing system even though the exposure control of the on-board camera is appropriate, and this may reduce the diagnosis accuracy for diagnosing malfunctions.